Grey-Level Cooccurrence Matrix Performance Evaluation for Heading Angle Estimation of Moveable Vision System in Static Environment

A method of extracting information in estimating heading angle of vision system is presented. Integration of grey-level cooccurrence matrix (GLCM) in an area of interest selection is carried out to choose a suitable region that is feasible for optical flow generation. The selected area is employed for optical flow generation by using Horn-Schunck method. From the generated optical flow, heading angle is estimated and enhanced via moving median filter (MMF). In order to ascertain the effectiveness of GLCM, we compared the result with a different estimation method of optical flow which is generated directly from untouched greyscale images. The performance of GLCM is compared to the true heading, and the error is evaluated through mean absolute deviation (MAE). The result ensured that GLCM can improve the estimation result of the heading angle of vision system significantly

Effect of contour interval on minimization of tool path length in pocket milling process

Reduction of machining time in the pocket machining process is important in order to enhance performance and increase productivity. In this paper, the main objective is to decrease the roughing time in pocket milling process by investigating the effect of path interval caused by the uncut area in the pocket milling with sharp corner. Decreasing machining time in process of milling using contour parallel direction as a strategy of machining can be achieved by increasing the value of tool path interval. Though, increasing the tool path interval has caused the existence of an uncut area at the sharp corner. To remove this uncut area, an additional tool path length is generated. So, this paper is carried out to study the consequence of path interval upon the existence of uncut region and the impact to the path length of contour parallel. There were three different values of tool path interval chosen and set to study the consequence of cutting tool path interval on tool path length, which were 5.6 μm, 5.7 μm, and 5.9 μm. Ant colony algorithm was developed to minimise the additional path length. As a result, increasing the path interval has produced larger uncut region at the corner. However, it produced shorter additional tool path length which resulted in lower roughing time

Simultaneous Localization and Mapping and Tag-Based Navigation for Unmanned Aerial Vehicles

This paper presents navigation techniques for an Unmanned Aerial Vehicle (UAV) in a virtual simulation of an indoor environment using Simultaneous Localization and Mapping (SLAM) and April Tag markers to reach a target destination. In many cases, UAVs can access locations that are inaccessible to people or regular vehicles in indoor environments, making them valuable for surveillance purposes. This study employs the Robot Operating System (ROS) to simulate SLAM techniques using LIDAR and GMapping packages for UAV navigation in two different environments. In the Tag-based simulation, the input topic for April Tag in ROS is camera images, and the calibration of position with a tag is done through assigning a message to each ID and its marker image. On the other hand, navigation in SLAM was achieved using a global and local planner algorithm. For localization, an Adaptive Monte-Carlo Localization (AMCL) technique has been used to identify factors contributing to inconsistent mapping results, such as heavy computational load, grid mapping accuracy, and inadequate UAV localization. Furthermore, this study analyzed the April Tag-based navigation algorithm, which showed satisfactory outcomes due to its lighter computing requirements. It can be ascertained that by using ROS packages, the simulation of SLAM and Tag-based UAV navigation inside a building can be achieved. &nbsp

Simultaneous Localization and Mapping and Tag-Based Navigation for Unmanned Aerial Vehicles

This paper presents navigation techniques for an Unmanned Aerial Vehicle (UAV) in a virtual simulation of an indoor environment using Simultaneous Localization and Mapping (SLAM) and April Tag markers to reach a target destination. In many cases, UAVs can access locations that are inaccessible to people or regular vehicles in indoor environments, making them valuable for surveillance purposes. This study employs the Robot Operating System (ROS) to simulate SLAM techniques using LIDAR and GMapping packages for UAV navigation in two different environments. In the Tag-based simulation, the input topic for April Tag in ROS is camera images, and the calibration of position with a tag is done through assigning a message to each ID and its marker image. On the other hand, navigation in SLAM was achieved using a global and local planner algorithm. For localization, an Adaptive Monte-Carlo Localization (AMCL) technique has been used to identify factors contributing to inconsistent mapping results, such as heavy computational load, grid mapping accuracy, and inadequate UAV localization. Furthermore, this study analyzed the April Tag-based navigation algorithm, which showed satisfactory outcomes due to its lighter computing requirements. It can be ascertained that by using ROS packages, the simulation of SLAM and Tag-based UAV navigation inside a building can be achieved. &nbsp

Improved Heading Direction Interpretation Via Optical Flow Using Selected Region Of Interest

In this paper, a technique of motion processing and analysis based on optical flow to gather information of heading direction from a vision system is presented. Instead of using the complete frame to determine the heading direction, in this paper, a region of interest (ROI) is used to calculate the heading direction. The selection of this ROI is based on the vector's magnitude dispersion criteria. This value is used as a visual feedback to a control system. The performance of proposed technique is compared to the true heading and the error is evaluated using root mean square error (RMSE). From the results, it shows that by appropriate selection of the region where the information from the optical flow is used, the visual feedback information results in less overshoot and undershoot in terms of its response

Identifying Student-Focused Intervention Programmes through Discrimination Index

AbstractDiscrimination index is one of the quantitative methods that seek to differentiate between students of high and low achievement by analysing their answers to examination questions at the end of their learning process. This assessment is done based on specific objectives such as identifying the level of students understanding on what they had learnt. Through discrimination index, various intervention programmes that students focused on can be proposed. Intervention programme must be designed according to the level of achievement of the students in the different groups and not based on the overall students’ achievements of the particular cohort. This paper reports a study on discrimination index using index ratings on a final year design-based course at the Department of Mechanical and Material Engineering of Universiti Kebangsaan Malaysia. The calculated indices have been successful in identifying appropriate intervention programmes to suit students of low achievers in the course

Comparative Study of Non-Productive Tool Path Length for Contour Parallel Machining / Haslina Abdullah...[et al.]

Reduction of machining time is significant for increasing the efficiencies of a machining process. It can be minimized by the rise with the cutting speed or decrease the tool path length. This paper presents an optimization method of non-productive tool path length during contour parallel offset machining by minimizing the tool retraction based on Ant Colony Optimization (ACO). The optimization of the tool retraction is modeled as an application of the Travelling Salesman Problem (TSP). To assess the performance of the proposed method, the length of the non-productive tool path obtained by ACO is compared with traditional computer-aided manufacturing (CAM) software. It can be ascertained that the ACO method generates a non-productive tool path length that is approximately 20% better than the conventional method

Investigation of disruption management practices and environmental impact on Malaysian automotive supply chains: a case study approach

Much focus on managing a supply chain in the event of disruption has been on the financial consequences and the service level impact on the customers. The negative impact caused by the disruption could influence a company’s profit and market share. Nonetheless, the importance of the environmental impact consideration in the supply chain disruption management has not been emphasised in the existing literature despite research findings that highlight the impact of some resilient supply chain practices on its environmental sustainability. This paper aims to assess the relationship between supply chain mitigation and recovery practices and its environmental impact. To achieve this objective, a case study was employed where semi-structured interviews were conducted at selected automotive companies in Malaysia. The results show that most disruption mitigation and recovery practices of a supply chain have a medium impact on its environmental performance. In particular, the production process during supply disruption recovery has the highest influence on environmental performance in the form of waste generation and use of energy. The results of this study can be used by supply chain managers to focus their efforts in the right direction in order to achieve cost objectives, service levels and environmental goals during the management of disruptions

Simulation and control of a six degree of freedom lower limb exoskeleton

In this paper, the development of controlling a six Degree of Freedom (DOF) Lower Limb Exoskeleton (LLE) model using the Robot Operating System (ROS) is presented. Moreover, this work proposes a method to analyze kinematic properties and control of the LLE before the prototype. The model of the LLE is described using Extensible Markup Language (XML) programming in the Unified Robot Description Format (URDF). The dynamic equation of the six-DoF LLE is determined by using Newton-Euler. In addition, a Proposition-Integral- Derivative (PID) controller is established in a feedback closed-loop control system. The PID controller is tuned via Ziegler-Nichols (Z-N). The tuned PID controller is tested in the Gazebo environment to confirm the performance of the proposed method. The nodes and topics flow chart of the programmed 3-D model of the LLE is described. Furthermore, a desired angular trajectory based on the phase on walking is defined for each joint of the LLE. The result shows that the actual pursue the desired angular trajectory for each joint. The average and maximum error of the angular trajectories for all the joints are less than 0.05 radian. It can be ascertained that our developed LLE model in the Gazebo simulator can be used for giving an overview of the walking pattern